8332255

Sensor-Integrated Mirror for Determining Consumer Shopping Behavior

PublishedDecember 11, 2012
Assigneenot available in USPTO data we have
Technical Abstract

Patent Claims
21 claims

Legal claims defining the scope of protection, as filed with the USPTO.

1

1. A computer-implemented method for gathering consumer shopping preferences for merchandise items, the method comprising: gathering one or more sequential images of a consumer trying on a first wearable merchandise item in front of an image sensor at a point-of-decision location, wherein the merchandise item is not purchased later by the consumer; identifying, by the computer, the first merchandise item being worn by the consumer based on the images; determining, by the computer, a demographic group associated with the consumer based on the images; detecting, by the computer, behavior patterns indicating an interest level of the consumer based at least on information about the consumer's decision-making process from the images associated with the merchandise item that is not later purchased; determining, by the computer, a mapping between the identified consumer demographic group and the interest level for the identified merchandise item; producing, by the computer, a model which encodes the mapping; displaying to the consumer a first set of images of a variety of wearable merchandise items overlaid on an image of the consumer; and analyzing, by the computer, a second set of images of the consumer to detect additional behavior patterns of the consumer, wherein the second set of images of the consumer viewing the first set of images are captured by a second image sensor.

2

2. The computer-implemented method of claim 1 , further comprising: analyzing the one or more sequential images to identify a second merchandise item considered by the consumer; determining one or more matching characteristics between the first and second merchandise items; and determining a preference of the consumer for merchandise items based at least on the determined matching characteristics.

3

3. The computer-implemented method of claim 1 , wherein detecting the behavior patterns for the consumer comprises detecting one or more of the following: an eye gaze direction, an eye gesture, a body gesture, a facial expression, a time duration associated with the direction of an eye gaze, and a time duration of the consumer wearing the merchandise item.

4

4. The computer-implemented method of claim 3 , wherein detecting the behavior patterns for the consumer further comprises: determining a portion of the merchandise item being gazed upon by the consumer based in part on the determined eye gaze direction; and determining an interest level of the consumer for the portion of the merchandise item.

5

5. The computer-implemented method of claim 3 , wherein detecting the behavior patterns for the consumer further comprises: determining a correlation between two merchandise items that are worn simultaneously by the consumer.

6

6. The computer-implemented method of claim 1 , wherein identifying the merchandise item comprises performing one or more of the following operations: scanning a radio-frequency identification (RFID) tag, scanning a barcode, and extracting a feature from the one or more sequential Images.

7

7. The computer-implemented method of claim 1 , wherein determining the demographic group associated with the consumer includes determining one or more of: an age, a gender, an ethnicity, a physical appearance, a body characteristic, and a market segment.

8

8. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for gathering consumer shopping preferences for merchandise items, the method comprising: gathering one or more sequential images of a consumer trying on a first wearable merchandise item in front of an image sensor at a point-of-decision location, wherein the merchandise item is not purchased later by the consumer; identifying the first merchandise item being worn by the consumer based on the images; determining a demographic group associated with the consumer based on the images; detecting behavior patterns indicating an interest level of the consumer based at least on information about the consumer's decision-making process from the images associated with the merchandise item that is not later purchased; determining a mapping between the identified consumer demographic group and the interest level for the identified merchandise item; producing a model which encodes the mapping; displaying to the consumer a first set of images of a variety of wearable merchandise items overlaid on an image of the consumer; and analyzing a second set of images of the consumer to detect additional behavior patterns of the consumer, wherein the second set of images of the consumer viewing the first set of images are captured by a second image sensor.

9

9. The non-transitory computer-readable storage medium of claim 8 , further comprising: analyzing the one or more sequential images to identify a second merchandise item considered by the consumer; determining one or more matching characteristics between the first and second merchandise items; and determining a preference of the consumer for merchandise items based at least on the determined matching characteristics.

10

10. The non-transitory computer-readable storage medium of claim 8 , wherein detecting the behavior patterns for the consumer comprises detecting one or more of the following: an eye gaze direction, an eye gesture, a body gesture, a facial expression, a time duration associated with the direction of an eye gaze, and a time duration of the consumer wearing the merchandise item.

11

11. The non-transitory computer-readable storage medium of claim 10 , wherein detecting the behavior patterns for the consumer further comprises: determining a portion of the merchandise item being gazed upon by the consumer based in part on the determined eye gaze direction; and determining an interest level of the consumer for the portion of the merchandise item.

12

12. The non-transitory computer-readable storage medium of claim 10 , wherein detecting the behavior patterns for the consumer further comprises: determining a correlation between two merchandise items that are worn simultaneously by the consumer.

13

13. The non-transitory computer-readable storage medium of claim 8 , wherein identifying the merchandise item comprises performing one or more of the following operations: scanning a radio-frequency identification (RFID) tag, scanning a barcode, and extracting a feature from the one or more sequential images.

14

14. The non-transitory computer-readable storage medium of claim 8 , wherein determining the demographic group associated with the consumer includes determining one or more of: an age, a gender, an ethnicity, a physical appearance, a body characteristic, and a market segment.

15

15. An apparatus for gathering consumer shopping preferences for merchandise items, comprising: a computer system including a processor configured to: gather one or more sequential images of a consumer trying on a first wearable merchandise item in front of an image sensor at a point-of-decision location, wherein the merchandise item is not purchased later by the consumer; identify the first merchandise item being worn by the consumer based on the images; determine a demographic group associated with the consumer based on the images; detect behavior patterns indicating an interest level of the consumer based at least on information about the consumer's decision-making process from the images associated with the merchandise item that is not later purchased; determine a mapping between the identified consumer demographic group and the interest level for the identified merchandise item; produce a model which encodes the mapping; display to the consumer a first set of images of a variety of wearable merchandise items overlaid on an image of the consumer; and analyze a second set of images of the consumer to detect additional behavior patterns of the consumer, wherein the second set of images of the consumer viewing the first set of images are captured by a second image sensor.

16

16. The apparatus of claim 15 , wherein the computer system is further configured to: analyze the one or more sequential images to identify a second merchandise item considered by the consumer; determine one or more matching characteristics between the first and second merchandise items; and determine a preference of the consumer for merchandise items based at least on the determined matching characteristics.

17

17. The apparatus of claim 15 , wherein while detecting the behavior patterns for the consumer, the computer system is configured to detect one or more of the following: an eye gaze direction, an eye gesture, a body gesture, a facial expression, a time duration associated with the direction of an eye gaze, and a time duration of the consumer wearing the merchandise item.

18

18. The apparatus of claim 17 , wherein while detecting the behavior patterns for the consumer, the computer system is configured to: determine a portion of the merchandise item being gazed upon by the consumer based in part on the determined eye gaze direction; and determine an interest level of the consumer for the portion of the merchandise item.

19

19. The apparatus of claim 17 , wherein while detecting the behavior patterns for the consumer, the computer system is configured to: determine a correlation between two merchandise items that are worn simultaneously by the consumer.

20

20. The apparatus of claim 15 , further comprising one or more of: a radio-frequency identifier (RFID) reader, and a barcode scanner; wherein while identifying the merchandise item, the computer system is configured to perform one or more of the following operations: configuring the RFID reader to scan an RFID tag, configuring the barcode scanner to scan a barcode, and extracting a feature from the one or more sequential images.

21

21. The apparatus of claim 15 , wherein while determining the demographic group associated with the consumer, the computer system is configured to determine one or more of: an age, a gender, an ethnicity, a physical appearance, a body characteristic, and a market segment.

Patent Metadata

Filing Date

Unknown

Publication Date

December 11, 2012

Inventors

Maurice K. Chu
James M.A. Begole

Want to explore more patents?

Browse 5M+ US patents with plain-English claim translations and AI-generated analysis.

Citation & reuse

Analysis on this page is generated by Patentable — an AI-powered patent intelligence platform. AI-generated summaries, explanations, and analysis may be reused with attribution and a visible link back to the canonical URL below. Patent abstracts and claims are USPTO public domain.

Cite as: Patentable. “SENSOR-INTEGRATED MIRROR FOR DETERMINING CONSUMER SHOPPING BEHAVIOR” (8332255). https://patentable.app/patents/8332255

© 2026 Patentable. All rights reserved.

Patentable is a research and drafting-assistant tool, not a law firm, and does not provide legal advice. Documents we generate are drafts for review by a licensed patent attorney.